Journal of Textile Research ›› 2021, Vol. 42 ›› Issue (05): 162-167.doi: 10.13475/j.fzxb.20200801906

• Apparel Engineering • Previous Articles     Next Articles

Evaluation modelling for maturity in intelligent manufacturing for multi-type clothing factories

DU Jinsong1,2(), YU Yayun1, ZHAO Ni1, XIE Ziang1, FEI Zhonghua3, PAN Jingshu1   

  1. 1.College of Fashion and Design, Donghua University, Shanghai 200051, China
    2. Key Laboratory of Clothing Design and Technology, Ministry of Education, Donghua University, Shanghai 200051, China
    3. Zhejiang Semir Garment Co., Ltd., Wenzhou, Zhejiang 362000, China
  • Received:2020-08-03 Revised:2020-02-03 Online:2021-05-15 Published:2021-05-20

Abstract:

In order to regulate the intelligent manufacturing for factories making different types of clothing, 5 first-level indicators, 12 second-level indicators and 35 third-level evaluation indexing elements were used to construct the maturity evaluation model for intelligent manufacturing capacity, based on the multi-dimensional Analytic Network Process (ANP). Expert questionnaire was used to determine the weight relationship of the evaluation model indicators, and the ANP evaluation indicator modeling was carried out with the help of the Super Decision software. The newly constructed capability maturity evaluation model and the general model were compared and verified on the maturity of intelligent construction capabilities of different types of clothing enterprises. The results show that the newly constructed evaluation model can fully reflect the current status of the development of intelligent manufacturing in the clothing industry and can accurately reflects the overall development level of the enterprise's intelligent manufacturing with the construction of individual indicators. It can also help the enterprise to develop the application technology.

Key words: clothing intelligent manufacturing, capability maturity, comprehensive evaluation model, analytic network process, clothing factory

CLC Number: 

  • TS941.79

Tab.1

Different types of clothing enterprises intelligent manufacturing capability index"

各级指标组成 企业类型
一级环节要素 二级组成要素 三级功能要素 OEM ODM OBM
指标 评价值 指标 评价值 指标 评价值
设计 A 服装产品设计 A1 服装款式设计 A11
服装纸样CAD设计 A12
三维虚拟试衣 A13
设计数据库 A14
服装工艺设计 A2 工艺数据库 A21
生产仿真 A22
精益生产能力 A23
与其他系统集成 A3 CAD/PDM集成 A31
PLM/ERP集成 A32
生产 B 生产计划 B1 企业资源计划 B11
制造资源计划 B12
生产过程 B2 订单管理 B21
物料采购 B22
人员管理 B23
质量控制 B24
计划与调度 B25
生产作业 B26
生产可视化 B27
生产资源管理 B3 设备效率分析 B31
设备管理系统 B32
物流 C 智能仓储 C1 订单及库存控制 C11
货位管理 C13
入库与移库管理 C13
动态拣选与盘点 C14
智能物流 C2 设备控制系统 C21
路径控制系统 C22
仓储物流设备 C3 设施设备 C31
系统集成 C32
销售 D 供应链管控体系 D1 供应链管理 D11
企业信息门户 D2 供应商管理 D21
客户关系管理 D22
服务 E 客户服务 E1 客户个性化服务 E11
售后服务 E12
网络服务 E2 网络协同 E21
网络安全 E22

Fig.1

ANP evaluation model for the capability maturity of smart clothing factories"

Fig.2

Correlation network among indicators"

Tab.2

Comparison of index weights of production links in different types of enterprises"

层级 指标内容 指标权重
OEM ODM OBM
一级 生产 0.622 193 0.612 708 0.362 259
二级 生产计划 0.152 742 0.156 41 0.096 956
生产过程 0.457 896 0.423 315 0.265 251
生产资源管理 0.011 555 0.032 983 0.000 052
三级 企业资源计划 0.037 840 0.046 190 0.048 701
制造资源计划 0.114 902 0.110 220 0.048 255
订单管理 0.107 064 0.110 984 0.092 458
物料采购 0.105 089 0.096 848 0.064 034
人员管理 0.013 849 0.019 686 0.003 943
质量控制 0.008 755 0.005 977 0.005 051
计划与调度 0.082 306 0.072 297 0.048 017
生产作业 0.131 093 0.107 286 0.051 610
生产可视化 0.009 74 0.010 237 0.000 138
设备效率分析 0.009 238 0.017 226 0.000 017
设备管理系统 0.002 317 0.015 757 0.000 035

Fig.3

Comparison of analysis results of various enterprises' indicators"

Tab.3

Comparative analysis of evaluation results of different models"

服装企业 中国智能制造能力
成熟度评价模型
服装企业能力
成熟度评价模型
综合得分 等级评定 综合得分 等级评定
SM 0.67 未达1级 1.89 第1级
(计划级)
PF 4.66 第4级
(优化级)
9.12 第5级
(领先级)
BXN 3.68 第3级
(集成级)
7.69 第4级
(优化级)
[1] 秦德智, 胡宏. 企业技术创新能力成熟度模型研究[J]. 技术经济与管理研究, 2011(7):53-57.
QIN Dezhi, HU Hong. Research on the maturity model of enterprise technological innovation capability[J]. Technoeconomics and Management Research, 2011 (7):53-57.
[2] 李振轩. 工业4.0就绪度模型对我国智能工厂建设的启示[J]. 信息技术与标准化, 2018(4):26-28.
LI Zhenxuan. Inspiration of industry 4.0 readiness model to the construction of smart factory in my country[J]. Information Technology and Standardization, 2018(4):26-28.
[3] 王文炎, 刘辉, 肖爱斌, 等. 宇航元器件产品成熟度评价研究[J]. 质量与可靠性, 2017(5):24-29.
WANG Wenyan, LIU Hui, XIAO Aibin, et al. Research on product maturity evaluation of aerospace components[J]. Quality and Reliability, 2017(5):24-29.
[4] 胡红梅. 德国“工业 4.0”对我国两化深度融合的启示[N]. 中国经济时报, 2014-08-04(6).
HU Hongmei. The enlightenment of German "industry 4.0" on my country's deep integration of industrialization and industrialization[N]. China Economic Times, 2014-08-04(6).
[5] 贾根良. 第三次工业革命与新型工业化道路的新思维—来自演化经济学和经济史的视角[J]. 中国人民大学学报, 2013,27(2):43-52.
JIA Genliang. The third industrial revolution and the new thinking of the new industrialization road-from the viewpoint of evolutionary economics and economic history[J]. Journal of Renmin University of China, 2013,27(2):43-52.
[6] 佚名. 智能制造能力评价标准发布[J]. 工具技术, 2016,50(11):44.
YI Ming. Intelligent manufacturing capability evaluation standard released[J]. Tool Technology, 2016,50(11):44.
[7] 舒伟. 纺织智能制造任重而道远[J]. 纺织学报, 2017,38(10):184-186.
SHU Wei. Smart textile manufacturing has a long way to go[J]. Journal of Textile Research, 2017,38(10):184-186.
[8] 陈雁. 服装设计与工程学科发展趋势与关键议题[J]. 纺织学报, 2019,40(1):182-188.
CHEN Yan. Development trends and key issues of fashion design and engineering disciplines[J]. Journal of Textile Research, 2019,40(1):182-188.
[9] 辛国斌, 田世宏. 国家智能制造标准体系建设指南(2015年版)[M]. 北京: 电子工业出版社, 2016: 178-185.
XIN Guobin, TIAN Shihong. Guidelines for the construction of national intelligent manufacturing standard system (2015 edition)[M]. Beijing: Publishing House of Electronics Industry, 2016: 178-185.
[10] 刘蓓蓓, 董明. 基于网络层次分析法的工业4.0指数评价体系[J]. 上海管理科学, 2017,39(5):104-107.
LIU Beibei, DONG Ming. Industry 4.0 index evaluation system based on network analytic hierarchy process[J]. Shanghai Management Science, 2017,39(5):104-107.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!